62 citations · 201 across the 21 of their papers we have counts for
12 papers · 1 filter
Zero-Shot Heart Rate Variability Forecasting from Consumer Wearables Using Time Series Foundation Models
Luukas Peräkylä, Fahad Sohrab, Ville Hautamäki +3
Short-term Heart Rate Variability (HRV) forecasting could provide clinicians with actionable lead time for detecting autonomic dysfunction and adverse cardiac events. Consumer wear…
To Vaccinate or not to Vaccinate? Analyzing Power over the Pandemic
Tanveer Khan, Fahad Sohrab, Antonis Michalas +1
The COVID-19 pandemic has profoundly affected the normal course of life -- from lock-downs and virtual meetings to the unprecedentedly swift creation of vaccines. To halt the COVID…
Anomaly Detection in Smart Power Grids with Graph-Regularized MS-SVDD: a Multimodal Subspace Learning Approach
Thomas Debelle, Fahad Sohrab, Pekka Abrahamsson +1
Anomaly detection in smart power grids is a critical challenge due to the complexity, heterogeneity, and dynamic nature of sensor data streams. Existing one-class classification me…
Conformal Prediction on Quantifying Uncertainty of Dynamic Systems
Aoming Liang, Qi Liu, Lei Xu +4
Numerous studies have focused on learning and understanding the dynamics of physical systems from video data, such as spatial intelligence. Artificial intelligence requires quantit…
Refining Myocardial Infarction Detection: A Novel Multi-Modal Composite Kernel Strategy in One-Class Classification
Muhammad Uzair Zahid, Aysen Degerli, Fahad Sohrab +4
Early detection of myocardial infarction (MI), a critical condition arising from coronary artery disease (CAD), is vital to prevent further myocardial damage. This study introduces…
Credit Card Fraud Detection with Subspace Learning-based One-Class Classification
Zaffar Zaffar, Fahad Sohrab, Juho Kanniainen +1
In an increasingly digitalized commerce landscape, the proliferation of credit card fraud and the evolution of sophisticated fraudulent techniques have led to substantial financial…
One-Class Classification for Intrusion Detection on Vehicular Networks
Jake Guidry, Fahad Sohrab, Raju Gottumukkala +2
Controller Area Network bus systems within vehicular networks are not equipped with the tools necessary to ward off and protect themselves from modern cyber-security threats. Work…
Convolutional autoencoder-based multimodal one-class classification
Firas Laakom, Fahad Sohrab, Jenni Raitoharju +2
One-class classification refers to approaches of learning using data from a single class only. In this paper, we propose a deep learning one-class classification method suitable fo…
Newton Method-based Subspace Support Vector Data Description
Fahad Sohrab, Firas Laakom, Moncef Gabbouj
In this paper, we present an adaptation of Newton's method for the optimization of Subspace Support Vector Data Description (S-SVDD). The objective of S-SVDD is to map the original…
Graph-Embedded Subspace Support Vector Data Description
Fahad Sohrab, Alexandros Iosifidis, Moncef Gabbouj +1
In this paper, we propose a novel subspace learning framework for one-class classification. The proposed framework presents the problem in the form of graph embedding. It includes…
Ellipsoidal Subspace Support Vector Data Description
Fahad Sohrab, Jenni Raitoharju, Alexandros Iosifidis +1
In this paper, we propose a novel method for transforming data into a low-dimensional space optimized for one-class classification. The proposed method iteratively transforms data…
Multimodal Subspace Support Vector Data Description
Fahad Sohrab, Jenni Raitoharju, Alexandros Iosifidis +1
In this paper, we propose a novel method for projecting data from multiple modalities to a new subspace optimized for one-class classification. The proposed method iteratively tran…